code: def after_loss(self):
      if not self.training:
          self.model.eval()
          with torch.no_grad():
              self.learn.raw_preds = self.model.forward_test(self.xb)
          self.model.train()
  
          # TODO: implement abstract function
          self.learn.converted_preds = self.convert_raw_predictions(
              batch=self.xb[0],
              raw_preds=self.raw_preds,
              records=self.records,
          )
  
file_path: icevision/icevision/models/mmseg/fastai/callbacks.py
imports: from icevision.imports import *
  from icevision.utils import *
  from icevision.core import *
  from icevision.data import *
  from icevision.engines.fastai import *
  from icevision.models.mmseg.utils import *
  from icevision.models.mmseg.common.prediction import convert_raw_predictions
label_desc: Use image node_id 4 for calling the MMSegmentationCallback obj's underlying member method code with example usage: obj.after_loss() without return types